Automatic quantification of morphological features for hepatic trabeculae analysis in stained liver specimens

Ishikawa, Masahiro; Murakami, Yuri; Ahi, Sercan Taha; Yamaguchi, Masahiro; Kobayashi, Naoki; Kiyuna, Tomoharu; Yamashita, Yugo; Saito, Akira; Abe, Tokiya; Hashiguchi, Akinori; Sakamoto, Michiie

doi:10.1117/1.jmi.3.2.027502

Cited by 12 publications

(10 citation statements)

References 22 publications

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“…The introduction of WSI to acquire images from HCC ( Figure 1) has motivated different groups to design algorithms for automatically grading HCC biopsies (28)(29)(30)(31)(32). Wholeslide images have been analyzed by software that recognizes differences and patterns in the image pixels indicative of specific HCC cell alterations in the nuclear area, circularity, and texture of hepatocytes; nuclear-cytoplasmic ratio and/or hepatic trabecular thickness.…”

Section: Wsi In Hepatocellular Carcinoma Diagnosismentioning

confidence: 99%

Whole Slide Imaging and Its Applications to Histopathological Studies of Liver Disorders

et al. 2020

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Histological analysis of hepatic tissue specimens is essential for evaluating the pathology of several liver disorders such as chronic liver diseases, hepatocellular carcinomas, liver steatosis, and infectious liver diseases. Manual examination of histological slides on the microscope is a classically used method to study these disorders. However, it is considered time-consuming, limited, and associated with intra-and inter-observer variability. Emerging technologies such as whole slide imaging (WSI), also termed virtual microscopy, have increasingly been used to improve the assessment of histological features with applications in both clinical and research laboratories. WSI enables the acquisition of the tissue morphology/pathology from glass slides and translates it into a digital form comparable to a conventional microscope, but with several advantages such as easy image accessibility and storage, portability, sharing, annotation, qualitative and quantitative image analysis, and use for educational purposes. WSI-generated images simultaneously provide high resolution and a wide field of observation that can cover the entire section, extending any single field of view. In this review, we summarize current knowledge on the application of WSI to histopathological analyses of liver disorders as well as to understand liver biology. We address how WSI may improve the assessment and quantification of multiple histological parameters in the liver, and help diagnose several hepatic conditions with important clinical implications. The WSI technical limitations are also discussed.

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Section: Wsi In Hepatocellular Carcinoma Diagnosismentioning

confidence: 99%

Whole Slide Imaging and Its Applications to Histopathological Studies of Liver Disorders

et al. 2020

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“…Sensitivity is related to the ability of the analysis to accurately exclude a condition, and is expressed in Eq. (10). Specificity is related to the ability of the analysis to accurately exclude a condition, and is expressed in Eq.…”

Section: Evaluation Metricsmentioning

confidence: 99%

“…A texture analysis method for cell nuclei has also been proposed for cancer detection [8]. Since RGB images of pathology specimens provide insufficient information for cancer diagnosis, other methods have been proposed in quantifying steatosis [9] and cell cord besides cell nuclei [10]. A texture analysis method that takes advantage of multifractal properties has also been proposed [11].…”

Section: Introductionmentioning

confidence: 99%

Detection of pancreatic tumor cell nuclei via a hyperspectral analysis of pathological slides based on stain spectra

Ishikawa¹,

Okamoto²,

Shinoda³

et al. 2019

Biomed. Opt. Express

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Hyperspectral imaging (HSI) provides more detailed information than red-green-blue (RGB) imaging, and therefore has potential applications in computer-aided pathological diagnosis. This study aimed to develop a pattern recognition method based on HSI, called hyperspectral analysis of pathological slides based on stain spectrum (HAPSS), to detect cancers in hematoxylin and eosin-stained pathological slides of pancreatic tumors. The samples, comprising hyperspectral cubes of 420-750 nm, were harvested for HSI and tissue microarray (TMA) analysis. As a result of conducting HAPSS experiments with a support vector machine (SVM) classifier, we obtained maximal accuracy of 94%, a 14% improvement over the widely used RGB images. Thus, HAPSS is a suitable method to automatically detect tumors in pathological slides of the pancreas.

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“…Even scarcer are studies evaluating the centrilobular fibrosis and, to the best of our knowledge, no standardized sinusoidal lumen area quantification method has been described with Masson's trichrome-stained livers specimens 13 .…”

Section: Introductionmentioning

confidence: 99%

“…In recent years, digital image technologies have been introduced to pathology diagnosis, allowing an objective quantitative assessment, more accurate rather than instead of the qualitative or semi-quantitative analysis that have been done in the conventional visual assessment 13 , 19 , 28 .…”

Section: Introductionmentioning

confidence: 99%

Software-Assisted Image Analysis for Identification and Quantification of Hepatic Sinusoidal Dilatation and Centrilobular Fibrosis

Gewehr

Giovanini

Munhoz

et al. 2021

ABCD, arq. bras. cir. dig.

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Background: Heart dysfunction and liver disease often coexist because of systemic disorders. Any cause of right ventricular failure may precipitate hepatic congestion and fibrosis. Digital image technologies have been introduced to pathology diagnosis, allowing an objective quantitative assessment. The quantification of fibrous tissue in liver biopsy sections is extremely important in the classification, diagnosis and grading of chronic liver disease. Aim: To create a semi-automatic computerized protocol to quantify any amount of centrilobular fibrosis and sinusoidal dilatation in liver Masson’s Trichrome-stained specimen. Method: Once fibrosis had been established, liver samples were collected, histologically processed, stained with Masson’s trichrome, and whole-slide images were captured with an appropriated digital pathology slide scanner. After, a random selection of the regions of interest (ROI’s) was conducted. The data were subjected to software-assisted image analysis (ImageJ®). Results: The analysis of 250 ROI’s allowed to empirically obtain the best application settings to identify the centrilobular fibrosis (CF) and sinusoidal lumen (SL). After the establishment of the colour threshold application settings, an in-house Macro was recorded to set the measurements (fraction area and total area) and calculate the CF and SL ratios by an automatic batch processing. Conclusion: Was possible to create a more detailed method that identifies and quantifies the area occupied by fibrous tissue and sinusoidal lumen in Masson’s trichrome-stained livers specimens.

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Automatic quantification of morphological features for hepatic trabeculae analysis in stained liver specimens

Cited by 12 publications

References 22 publications

Whole Slide Imaging and Its Applications to Histopathological Studies of Liver Disorders

Whole Slide Imaging and Its Applications to Histopathological Studies of Liver Disorders

Detection of pancreatic tumor cell nuclei via a hyperspectral analysis of pathological slides based on stain spectra

Software-Assisted Image Analysis for Identification and Quantification of Hepatic Sinusoidal Dilatation and Centrilobular Fibrosis

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